Dropping the E: The potential for integrating e-mental health in psychotherapy

Additive effects of adjunctive app-based interventions for mental disorders - A systematic review and meta-analysis of randomised controlled trials

Background

It is uncertain whether app-based interventions add value to existing mental health care.

Objective

To examine the incremental effects of app-based interventions when used as adjunct to mental health interventions.

Methods

We searched PubMed, PsycINFO, Scopus, Web of Science, and Cochrane Library databases on September 15th, 2023, for randomised controlled trials (RCTs) on mental health interventions with an adjunct app-based intervention compared to the same intervention-only arm for adults with mental disorders or respective clinically relevant symptomatology. We conducted meta-analyses on symptoms of different mental disorders at postintervention. PROSPERO, CRD42018098545.

Results

We identified 46 RCTs (4869 participants). Thirty-two adjunctive app-based interventions passively or actively monitored symptoms and behaviour, and in 13 interventions, the monitored data were sent to a therapist. We found additive effects on symptoms of depression (g = 0.17; 95 % CI 0.02 to 0.33; k = 7 comparisons), anxiety (g = 0.80; 95 % CI 0.06 to 1.54; k = 3), mania (g = 0.2; 95 % CI 0.02 to 0.38; k = 4), smoking cessation (g = 0.43; 95 % CI 0.29 to 0.58; k = 10), and alcohol use (g = 0.23; 95 % CI 0.08 to 0.39; k = 7). No significant effects were found on symptoms of depression within a bipolar disorder (g = -0.07; 95 % CI -0.37 to 0.23, k = 4) and eating disorders (g = -0.02; 95 % CI -0.44 to 0.4, k = 3). Studies on depression, mania, smoking, and alcohol use had a low heterogeneity between the trials. For other mental disorders, only single studies were identified. Only ten studies had a low risk of bias, and 25 studies reported insufficient statistical power.

Discussion

App-based interventions may be used to enhance mental health interventions to further reduce symptoms of depression, anxiety, mania, smoking, and alcohol use. However, the effects were small, except for anxiety, and limited due to study quality. Further high-quality research with larger sample sizes is warranted to better understand how app-based interventions can be most effectively combined with established interventions to improve outcomes.

Adjusting to a new reality: Consensual qualitative research on therapists' experiences with teletherapy

OBJECTIVE

In the wake of the COVID-19 pandemic, the use of teletherapy has become more pervasive than ever. Many therapists faced this move to a remote setting with little experience or training. We aimed to qualitatively examine therapists' subjective experience of providing teletherapy, including changes in technique, the therapeutic relationship, and the therapeutic process.

METHODS

Thirty-one psychotherapists participated in semistructured interviews. Interviews were recorded, then transcribed and analyzed using the Consensual Qualitative Research method.

RESULTS

Therapists typically reported a change in the therapeutic relationship in terms of an increased sense of disconnection as well as shifts in various aspects of the relational dynamics, and they also typically experienced differences in the therapy process due to changes in patient and therapist engagement in the therapeutic work. Additionally, some therapists also reported that they became more active and directive in sessions, took a more informal, personal, or relaxed approach to interacting with patients, and while the emotional connection changed and they missed the energy and intimacy of in-person sessions, the relationship in telesessions felt more authentic and human for some, and teletherapy also provided a way to discuss new dimensions in the process.

CONCLUSION

Overall, these results suggest great variability in therapists' subjective experiences with teletherapy, and present teletherapy as a distinct therapy format in many aspects. Further process-level research and subsequent training is needed to better equip therapists to navigate teletherapy's challenges and harness its unique opportunities.

The feasibility of using Apple's ResearchKit for recruitment and data collection: Considerations for mental health research

In 2015, Apple launched an open-source software framework called ResearchKit. ResearchKit provides an infrastructure for conducting remote, smartphone-based research trials through the means of Apple's App Store. Such trials may have several advantages over conventional trial methods including the removal of geographic barriers, frequent assessments of participants in real-life settings, and increased inclusion of seldom-heard communities. The aim of the current study was to explore the feasibility of participant recruitment and the potential for data collection in the non-clinical population in a smartphone-based trial using ResearchKit. As a case example, an app called eMovit, a behavioural activation (BA) app with the aim of helping users to build healthy habits was used. The study was conducted over a 9-month period. Any iPhone user with access to the App Stores of The Netherlands, Belgium, and Germany could download the app and participate in the study. During the study period, the eMovit app was disseminated amongst potential users via social media posts (Twitter, Facebook, LinkedIn), paid social media advertisements (Facebook), digital newsletters and newspaper articles, blogposts and other websites. In total, 1,788 individuals visited the eMovit landing page. A total of 144 visitors subsequently entered Apple's App Store through that landing page. The eMovit product page was viewed 10,327 times on the App Store. With 79 installs, eMovit showed a conversion rate of 0.76% from product view to install of the app. Of those 79 installs, 53 users indicated that they were interested to participate in the research study and 36 subsequently consented and completed the demographics and the participants quiz. Fifteen participants completed the first PHQ-8 assessment and one participant completed the second PHQ-8 assessment. We conclude that from a technological point of view, the means provided by ResearchKit are well suited to be integrated into the app process and thus facilitate conducting smartphone-based studies. However, this study shows that although participant recruitment is technically straightforward, only low recruitment rates were achieved with the dissemination strategies applied. We argue that smartphone-based trials (using ResearchKit) require a well-designed app dissemination process to attain a sufficient sample size. Guidelines for smartphone-based trial designs and recommendations on how to work with challenges of mHealth research will ensure the quality of these trials, facilitate researchers to do more testing of mental health apps and with that enlarge the evidence-base for mHealth.

Online consultations in mental healthcare: Modelling determinants of use and experience based on an international survey study at the onset of the pandemic

INTRODUCTION

While online consultations have shown promise to be a means for the effective delivery of high-quality mental healthcare and the first implementations of these digital therapeutic contacts go back nearly two decades, uptake has remained limited over the years. The onset of the COVID-19 pandemic dramatically altered this relative standstill and created a unique turning point, with a massive amount of both professionals and clients having first hands-on experiences with technology in mental healthcare.

OBJECTIVE

The current study aimed to document the uptake of online consultations and explore if specific characteristics of mental health professionals across and beyond Europe could predict this.

METHODS

An international survey was designed to assess mental health professionals' (initial) experiences with online consultations at the onset of the pandemic: their willingness to make use of them and their prior and current experiences, alongside several personal characteristics. Logistic mixed-effects models were used to identify predictors of the use of online consultations, personal experience with this modality, and the sense of telepresence.

RESULTS

A total of 9115 healthcare professionals from 73 countries participated of which about two-thirds used online consultations during the initial COVID-19 outbreak. The current study identifies multiple determinants relating to the use and experience of online consultations, including the professionals' age, experience with the technology before the outbreak, the professional context, and training.

CONCLUSIONS

Despite strong evidence supporting the relevance of training in digital mental health, this is clearly still lacking. Nevertheless, the COVID-19 pandemic presented a first, and potentially transformative, experience with online consultations for many healthcare professionals. The insights from this study can help support professionals and, importantly, (mental) healthcare organisations to create optimal circumstances for selective and high-quality continued use of online consultations.

Psychotherapists' acceptance of telepsychotherapy during the COVID-19 pandemic: A machine learning approach

Objective

This study aimed to develop predictive models of three aspects of psychotherapists' acceptance of telepsychotherapy (TPT) during the COVID‐19 pandemic, attitudes towards TPT technology, concerns about using TPT technology and intention to use TPT technology in the future.

Method

Therapists (n = 795) responded to a survey about their TPT experiences during the pandemic, including quality of the therapeutic relationship, professional self‐doubt, vicarious trauma and TPT acceptance. Regression decision tree machine learning analyses were used to build prediction models for each of three aspects of TPT acceptance in a training subset of the data and subsequently tested in the remaining subset of the total sample.

Results

Attitudes towards TPT were most positive for therapists who reported a neutral or strong online working alliance with their patients, especially if they experienced little professional self‐doubt and were younger than 40 years old. Therapists who were most concerned about TPT were those who reported higher levels of professional self‐doubt, particularly if they also reported vicarious trauma experiences. Therapists who reported low working alliance with their patients were least likely to use TPT in the future. Performance metrics for the decision trees indicated that these three models held up well in an out‐of‐sample dataset.

Conclusions

Therapists' professional self‐doubt and the quality of their working alliance with their online patients appear to be the most pertinent factors associated with therapists' acceptance of TPT technology during COVID‐19 and should be addressed in future training and research.

Validity and Reliability of the Self-administered Psycho-TherApy-SystemS (SELFPASS) Item Pool for the Daily Mood Tracking of Depressive Symptoms: Cross-sectional Web-Based Survey

BACKGROUND

e-Mental health apps targeting depression have gained increased attention in mental health care. Daily self-assessment is an essential part of e-mental health apps. The Self-administered Psycho-TherApy-SystemS (SELFPASS) app is a self-management app to manage depressive and comorbid anxiety symptoms of patients with a depression diagnosis. A self-developed item pool with 40 depression items and 12 anxiety items is included to provide symptom-specific suggestions for interventions. However, the psychometric properties of the item pool have not yet been evaluated.

OBJECTIVE

The aim of this study is to investigate the validity and reliability of the SELFPASS item pool.

METHODS

A weblink with the SELFPASS item pool and validated mood assessment scales was distributed to healthy subjects and patients who had received a diagnosis of a depressive disorder within the last year. Two scores were derived from the SELFPASS item pool: SELFPASS depression (SP-D) and SELFPASS anxiety (SP-A). Reliability was examined using Cronbach α. Construct validity was assessed through Pearson correlations with the Patient Health Questionnaire-9 (PHQ-9), the General Anxiety Disorder Scale-7 (GAD-7), and the WHO-5-Wellbeing-Scale (WHO-5). Logistic regression analysis was performed as an indicator for concurrent criterion validity of SP-D and SP-A. Factor analysis was performed to provide information about the underlying factor structure of the item pool. Item-scale correlations were calculated in order to determine item quality.

RESULTS

A total of 284 participants were included, with 192 (67.6%) healthy subjects and 92 (32.4%) patients. Cronbach α was set to .94 for SP-D and α=.88 for SP-A. We found significant positive correlations between SP-D and PHQ-9 scores (r=0.87; P<.001) and between SP-A and GAD-7 scores (r=0.80; P<.001), and negative correlations between SP-D and WHO-5 scores (r=-0.80; P<.001) and between SP-A and WHO-5 scores (r=-0.69; P<.001). Increasing scores of SP-D and SP-A led to increased odds of belonging to the patient group (SP-D: odds ratio 1.03, 95% CI 1.01-1.05; P<.001; SP-A: 1.05, 1.05-1.01; P=.01). The item pool yielded 2 factors: one that consisted of mood-related items and another with somatic-related items.

CONCLUSIONS

The SELFPASS item pool showed good psychometric properties in terms of reliability, construct, and criterion validity. The item pool is an appropriate source for daily mood tracking in future e-mental health apps among patients with depression. Our study provides general recommendations for future developments as well as recommendations within the item pool.